Higher order texture statistics impair contrast boundary segmentation.

نویسندگان

  • Elizabeth Arsenault
  • Ahmad Yoonessi
  • Curtis Baker
چکیده

Texture boundary segmentation is conventionally thought to be mediated by global differences in Fourier energy, i.e., low-order texture statistics. Here, we have examined the importance of higher order statistical structure of textures in a simple second-order segmentation task. We measured modulation depth thresholds for contrast boundaries imposed on texture samples extracted from natural scene photographs, using forced-choice judgments of boundary orientation (left vs. right oblique). We compared segmentation thresholds for contrast boundaries whose constituent textures were either intact or phase scrambled. In the intact condition, all the texture statistics were preserved, while in the phase-scrambled condition the higher order statistics of the same texture were randomized, but the lower order statistics were unchanged. We found that (1) contrast boundary segmentation is impaired by the presence of higher order statistics; (2) every texture shows impairment but some substantially more than others; and (3) our findings are not related to scrambling-induced changes in detectability. The magnitude of phase-scrambling effect for individual textures was uncorrelated with variations in their amplitude spectra, but instead we suggest that it might be related to differences in local edge structure or sparseness.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Texture sparseness, but not local phase structure, impairs second-order segmentation

Texture boundary segmentation is typically thought to reflect a comparison of differences in Fourier energy (i.e. low-order texture statistics) on either side of a boundary. However in a previous study (Arsenault, Yoonessi, & Baker, 2011) we showed that the distribution of energy within a natural texture (i.e. its higher-order statistical structure) also influences segmentation of contrast boun...

متن کامل

Higher order image structure enables boundary segmentation in the absence of luminance or contrast cues.

Lower order image statistics, which can be described by an image's Fourier energy content, enable segmentation when they are different on either side of a boundary. We have previously demonstrated that the spatial distribution of the energy in an image (described by its higher order statistics or structure) could influence segmentation thresholds for contrast- and orientation-defined boundaries...

متن کامل

Significantly Different Textures: A Computational Model of Pre-attentive Texture Segmentation

Recent human vision research [1] suggests modelling preattentive texture segmentation by taking a set of feature samples from a local region on each side of a hypothesized edge, and then performing standard statistical tests to determine if the two samples differ significantly in their mean or variance. If the difference is significant at a specified level of confidence, a human observer will t...

متن کامل

Texture Segmentation Using Semi-supervised Support Vector Machine

Support vector machine (SVM) is used here to detect the texture boundaries. In order to do that, a cost function is initially defined based on the estimation of higher order statistics (HOS) of the intensities within small regions. K-mean algorithm is used to find the centres of the two clusters (boundary or texture) from the values of the cost function over the entire image. Then the target va...

متن کامل

Supervised Texture Classification for Segmentation of Abnormal Lung in Ct

Delineation of lung fields in presence of diffuse lung diseases, such as interstitial pneumonias (IP), challenges conventional gray level based segmentation algorithms. To deal with IP patterns affecting lung borders, a texture classification scheme for lung segmentation is proposed. The proposed method is based on supervised texture classification to distinguish surrounding tissue (ST) from lu...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Journal of vision

دوره 11 10  شماره 

صفحات  -

تاریخ انتشار 2011